A Data Augmentation Method for Shearer Rocker Arm Bearing Fault Diagnosis Based on GA-WT-SDP and WCGAN

This work addresses the challenges of inadequate data acquisition and the limited availability of labeled samples for shearer rocker arm bearing faults by developing a data augmentation methodology that synergistically incorporates the Genetic Algorithm-optimized Wavelet Transform Symmetrical Dot Pa...

詳細記述

書誌詳細

主要な著者:	Zhaohong Wu, Shuo Wang, Chang Liu, Haiyang Wu, Jiang Yi, Yusong Pang, Gang Cheng
フォーマット:	Artigo
言語:	Inglês
出版事項:	MDPI AG 2026-01-01
シリーズ:	Machines
主題:	rearing data augmentation fault diagnosis genetic algorithms wasserstein conditional gAN
オンライン･アクセス:	https://www.mdpi.com/2075-1702/14/2/144
タグ:	タグ追加 タグなし, このレコードへの初めてのタグを付けませんか!